Deep-active-learning approach towards accurate right ventricular segmentation using a two-level uncertainty estimation.

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作者： Asma,Ammari ^[1] ; Ramzi,Mahmoudi ^[2] ; Badii,Hmida ^[3] ; Rachida,Saouli ^[4] ; Mohamed,Hedi Bedoui ^[5]

作者单位： Medical Imaging Technology Laboratory, Faculty of Medicine, LTIM-LR12ES06, University of Monastir, 5019 Monastir, Tunisia; Laboratory of Intelligent Computing (LINFI), Department of Computer Science, Mohamed Khider University, BP 145 RP, Biskra 07000, Algeria; The National Engineering School ENIS, Sfax, Tunisia. Electronic address: asma.ammari@univ-biskra.dz. ^[1] Medical Imaging Technology Laboratory, Faculty of Medicine, LTIM-LR12ES06, University of Monastir, 5019 Monastir, Tunisia; Gaspard-Monge Computer-science Laboratory, Paris-Est University, Mixed Unit CNRS-UMLV-ESIEE UMR8049, BP99, ESIEE Paris City Descartes, 93162 Noisy Le Grand, France. ^[2] Medical Imaging Technology Laboratory, Faculty of Medicine, LTIM-LR12ES06, University of Monastir, 5019 Monastir, Tunisia; Radiology Service, UR12SP40 CHU Fattouma Bourguiba, 5019 Monastir, Tunisia. ^[3] Laboratory of Intelligent Computing (LINFI), Department of Computer Science, Mohamed Khider University, BP 145 RP, Biskra 07000, Algeria. ^[4] Medical Imaging Technology Laboratory, Faculty of Medicine, LTIM-LR12ES06, University of Monastir, 5019 Monastir, Tunisia. ^[5]

关键词 Aleatoric uncertainty Cardiac magnetic resonance imaging Deep active learning Epistemic uncertainty Right ventricular segmentation

主题词人类(Humans);心室(Heart Ventricles);基于问题的学习(Problem-Based Learning);偏差(Uncertainty);图像处理, 计算机辅助(Image Processing, Computer-Assisted);磁共振成像(Magnetic Resonance Imaging)

DOI 10.1016/j.compmedimag.2022.102168

PMID 36640486

发布时间 2023-04-07

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